Intelligent lower limb feedback training system and method with balance training function

Abstract

The invention belongs to the field of medical equipment, and particularly relates to a lower limb intelligent feedback training system and method with balance training, and the method comprises the steps that a pressure feedback system monitors the pressure applied by a left foot and a right foot to corresponding pedals in the stepping training process of a patient, and sends the obtained pressure value to an electric control system; the execution mechanism realizes height lifting, lying standing, foot plate stretching and backrest posture adjustment of the bed body according to a control instruction of the electric control system, and meanwhile, controls left and right pedal plates to execute reciprocating motion; the electric control system receives training control parameters issued by the upper computer and controls the execution mechanism to execute corresponding motion; the running state of the training motor, the running state of each push rod, the training coordination of the left leg and the right leg and the collected pressure value are sent to an upper computer in real time; and meanwhile, the information is displayed on the man-machine interaction system. By detecting the plantar pressure in the walking process of the two feet, balance analysis is carried out when the left foot and the right foot walk, and abnormal gaits are prevented from being generated after walking is recovered.

Description

Technical Field

[0001] The invention belongs to the field of medical equipment, and in particular to a lower limb intelligent feedback training system and method with balance training. Background Art

[0002] There are about 3 million new stroke cases in my country every year, of which about 75% of stroke patients have sequelae of limb disability, and eventually lose the ability to walk and cannot live independently. In order to enable these patients with lower limb disability to recover their walking ability as soon as possible, the design of the lower limb intelligent feedback training system allows patients with lower limb disability to conduct rehabilitation training in a relaxed state and restore walking function as soon as possible. At the same time, it also reduces the physical and psychological burden of family members or caregivers assisting patients in walking training, and also reduces the accidental risks of disabled patients during the recovery training process.

[0003] The lower limb intelligent feedback training system is suitable for bedridden patients in the acute stage of neurological rehabilitation. It changes the patient from lying to standing position, avoiding complications such as osteoporosis, postural hypotension, bedsores, and muscle atrophy caused by long-term bed rest. It has the functions of improving cardiopulmonary function, maintaining human stress load, preventing urine retention, and promoting metabolism of the lower limbs and even the whole body. Through active and passive stepping exercise training, it simulates the physiological gait of the human body during normal walking, restores the patient's walking function to the highest degree, and inhibits abnormal gait. It helps patients establish a correct walking pattern in early rehabilitation training.

[0004] However, in most of the lower limb intelligent feedback training systems currently used in rehabilitation institutions, during the patient training process, doctors can only observe the patient's walking status for a long time, make subjective judgments based on experience, or score based on clinical evaluation scales. This method is not only inefficient and subjective, but also has no reliable test data support, which has an adverse effect on the judgment of the patient's rehabilitation status and the adjustment of the treatment plan. Summary of the invention

[0005] The purpose of the present invention is to design a lower limb intelligent feedback training system with balance training for rehabilitation treatment of patients with lower limb dysfunction caused by nervous system damage such as stroke. The system adopts a combination of active and passive training methods, and accurately controls the stepping movement according to the physiological gait curve of the human body, so that the patient can gradually "walk" and restore the walking function. At the same time, during the training process, the plantar pressure of the two feet is detected during the stepping process, and the balance analysis of the left and right feet when walking is performed to prevent abnormal gait after recovery of walking. At the same time, it reduces the burden on nursing staff and reduces nursing costs.

[0006] The technical solution adopted by the present invention to achieve the above-mentioned purpose is: a lower limb intelligent feedback training system with balance training, characterized in that it includes: an electric control system and an actuator connected to the electric control system, a pressure feedback system and a human-computer interaction system;

[0007] The pressure feedback system is used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training, and obtain the pressure value after processing and send it to the electronic control system;

[0008] The actuator is used to realize the height raising and lowering, lying and standing, footboard extension and retraction, and backrest posture adjustment of the bed according to the control instructions of the electronic control system, and at the same time, control the left and right foot pedals to perform reciprocating motion;

[0009] The human-computer interaction system is used to receive the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs, and display them in real time; at the same time, it dynamically provides situational interactive voice prompts to enable users to actively train, and uploads the user's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time;

[0010] The electronic control system is used to receive the training control parameters sent by the host computer and control the actuator to perform the corresponding movement; and send the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system to the host computer in real time; at the same time, the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs are displayed in real time on the human-computer interaction system.

[0011] The execution mechanism includes: a bed posture adjustment mechanism and a leg training execution mechanism;

[0012] The bed posture adjustment mechanism is used to control the movement of the bed according to the control instructions received from the electronic control system, thereby realizing the change of the bed posture;

[0013] The leg training execution mechanism is arranged at the rear of the bed body, and is used to operate and drive the left and right legs of the disabled patient to perform reciprocating motion according to the control instructions received from the electric control system.

[0014] The posture adjustment mechanism of the bed body includes: a bed body standing push rod, an overall lifting push rod, a leg adjustment push rod and a back adjustment push rod;

[0015] The fixed end of the bed stand-up push rod is installed on the liftable frame of the bed, and the telescopic end is installed on the bed board structure frame, which is used to receive the control command of the electric control system, execute the push rod telescopic action, and realize the posture change from lying flat to standing up for the disabled patient on the bed;

[0016] The fixed end of the integral lifting push rod is installed on the bottom frame of the bed, and the telescopic end is installed on the liftable frame. It is used to receive the control command of the electronic control system, execute the push rod telescopic action, and realize the overall height adjustment of the bed to avoid interference and collision between the leg length telescopic structure and the ground after the bed is standing up;

[0017] The fixed end of the leg adjustment push rod is installed on the bed structure frame, and the telescopic end is installed on the telescopic structure of the frame, which is used to receive the control command of the electronic control system, execute the telescopic movement of the push rod and change the position of the foot pedal, that is, change the distance between the foot pedal and the knee leggings;

[0018] The fixed end of the back adjustment push rod is installed on the bed board structure frame, and the telescopic end is installed on the pitchable structure of this frame. It is used to receive control instructions from the electronic control system, execute the extension and retraction of the push rod, and realize the backward posture adjustment of the back position of the bed board. That is, when the patient stands up on the bed board for training, the back leans backward, thereby obtaining a more comfortable body posture.

[0019] The leg training execution mechanism is provided with two driving motors corresponding to the left and right legs of the disabled patient, and connected to the left and right foot pedals respectively;

[0020] The drive motor receives control instructions from the electronic control system, and alternately causes the left and right foot pedals to reciprocate up and down, thereby driving the patient's legs to perform rehabilitation training for stepping and walking.

[0021] The electric control system includes: a core control board and a motor drive board, a push rod drive board, and a signal acquisition interface connected to the core control board;

[0022] The motor drive board is connected to the left and right motors of the leg training actuator to drive the left and right motors to reciprocate, drive the left and right foot pedals to reciprocate up and down, and then realize the rehabilitation training of the patient's legs to step and walk; at the same time, the motor drive board monitors the current of the motor in real time during operation to determine whether the patient has cramps during training. If cramps occur, the training is stopped and the motor is driven to perform slow reverse motion to relieve the cramps;

[0023] The push rod driving board is used to control the extension and contraction of the electric push rod, and monitor the Hall value of the push rod in real time, so as to judge the extension of each push rod, and analyze it into the angle and height of the corresponding bed structure, and display it in real time on the upper computer interface;

[0024] Signal acquisition interface, which is used as the data input interface of peripheral sensors, collects the status information of each module, the position status information of each structure, the pressure information of plantar training, and safety information in real time, and transmits it to the system core control board for analysis and processing;

[0025] The core control board is used to connect to the host computer through the host computer communication interface, and is used to send the operating status of the training motor, the operating status of each push rod, and the training coordination information of the left and right legs to the host computer, and at the same time receive the training control parameters sent by the host computer to control the actuator through the motor drive board and the push rod drive board.

[0026] The pressure feedback system comprises: a pressure signal amplifier board, a left leg pressure sensor and a right leg pressure sensor;

[0027] The left leg pressure sensor and the right leg pressure sensor are respectively installed on the pedals of the left and right legs, and are used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training. The pressure signal is then amplified by the pressure signal amplifier board and transmitted to the core control board of the electronic control system for calculation and analysis. By comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are analyzed, and a rehabilitation training plan is specified for the patient. At the same time, the pressure values ​​of the left and right legs are processed by the core control board and sent to the host computer. The pressure values ​​of the two legs will be displayed in real time on the training interface, and the patient's training gait will be displayed through the interface animation, thereby changing the uncoordinated stepping state.

[0028] The human-computer interaction system comprises: an interactive training module, a processor unit, a display screen, a visual training feedback module, an information storage module and a network transmission module;

[0029] The processor unit is used to receive the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and display them on the display screen; at the same time, adjust the interactive scenario and reallocate the training tasks based on the visual training feedback results sent by the visual training feedback module;

[0030] Interactive training software, installed on the processor unit, including: a situational interactive game module and a visual training feedback module;

[0031] The scenario interactive game module is used to provide scenario interactive voice prompts to enable users to actively train, and at the same time, execute the interactive scenarios adjusted by the processor unit and the reallocated training tasks;

[0032] A visual training feedback module is configured in the interactive training software and is used to capture the patient's visual movements during the patient training process and to feed back the visual training results to the processor unit;

[0033] An information storage module, disposed in the processor unit, for storing the patient's training information, including training status, training progress and rehabilitation status information;

[0034] The network transmission module is integrated in the processor unit and is used to upload the patient's training information to the host computer via Wi-Fi, so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

[0035] A training method of a lower limb intelligent feedback training system with balance training comprises the following steps:

[0036] 1) The electronic control system receives the training control parameters sent by the host computer, controls the actuators to perform the height adjustment, lying and standing, foot extension and retraction, backrest posture adjustment of the bed, and controls the left and right foot pedals to perform reciprocating motion, so as to realize the user's passive training;

[0037] 2) The electronic control system sends the acquired operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system to the host computer in real time;

[0038] 3) The core control board of the electronic control system sends the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs to the human-computer interaction system; at the same time, the pressure feedback system collects the pressure values ​​of the left and right legs of the left and right foot pedals, and sends them to the host computer and the human-computer interaction system after processing;

[0039] 4) The human-computer interaction system receives the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and displays them on the display screen;

[0040] 5) The human-computer interaction system also provides situational interactive voice prompts to enable users to complete active training, and uploads the patient's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

[0041] The pressure feedback system collects the pressure values ​​of the left and right legs of the left and right foot pedals, and sends them to the host computer and the human-computer interaction system respectively after processing, specifically:

[0042] (1) Pressure data collection and preprocessing:

[0043] The left leg pressure sensor and the right leg pressure sensor monitor the pressure on the pedal in real time at a fixed frequency to obtain raw pressure data; the high-frequency noise components of the raw pressure data are removed by a low-pass filtering algorithm, the pressure curve is smoothed, and the pressure data signal is obtained;

[0044] Normalize the filtered pressure data signal and map the data to a set value range to facilitate subsequent comparison and calculation;

[0045] (2) Pressure signal amplification and transmission:

[0046] The pre-processed pressure data is transmitted to the pressure signal amplifier board, which amplifies the pressure signal according to the preset amplification factor to improve the signal strength and resolution; the amplified pressure signal is transmitted to the core control board of the electronic control system;

[0047] (3) Core control board data reception and analysis:

[0048] After receiving the pressure signal from the amplifier board, the core control board parses the data according to the pre-set communication protocol, restores it to the pressure value information of the left and right legs, and stores it in the buffer for subsequent batch processing.

[0049] (4) Comparative analysis with the preset training model:

[0050] Read the left and right leg pressure data sequence within the set time period from the buffer, and calculate the characteristic parameters of the left and right legs, including the average pressure value, pressure peak value, pressure change rate, and pressure duration parameters;

[0051] Compare and analyze the characteristic parameters of the left and right legs with the standard parameters in the preset training model; the preset training model is established based on the stepping training data of healthy people and patients at different rehabilitation stages, and includes the normal range and change trend of the pressure parameters of the left and right legs at different rehabilitation levels;

[0052] The difference between the left and right leg pressure parameters and the standard parameters is calculated, and the distance between the eigenvectors is calculated using the Euclidean distance formula. The larger the distance, the greater the deviation from the standard state. At the same time, the correlation between the left and right leg pressure parameters is analyzed, and the coordination of the two legs during the stepping process is judged by calculating the covariance. If the covariance is close to 0, it means that the coordination is poor. If the covariance is positive and greater than the threshold, it means that the movements of the two legs are consistent and coordinated.

[0053] (5) Recovery status and coordination assessment:

[0054] According to the difference and correlation results obtained by comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are comprehensively evaluated; if the difference between the pressure parameters of one leg and the standard parameters is greater than the preset value and the other leg is relatively smaller than the preset value, it means that the recovery degree of one leg is relatively backward; if the difference between the pressure parameters of both legs is less than the preset value and the coordination is good, it indicates that the patient's overall recovery state is good; and the evaluation results are graded according to the preset grading standards;

[0055] (6) Development of rehabilitation training plan:

[0056] According to the recovery status and coordination assessment level of the patient's left and right legs, the core control panel selects a training plan from its built-in rehabilitation training plan library; the selected rehabilitation training plan is notified to the patient and the rehabilitation therapist through the display screen or voice prompts, and the patient performs subsequent stepping training according to the plan. During the training process, the system continuously monitors pressure data and adjusts the training plan in real time to adapt to the patient's rehabilitation progress.

[0057] The step 5) is specifically:

[0058] a. The scenario interactive game module provides users with scenario interactive voice prompts, and users complete active training according to the voice prompts. At the same time, the visual training feedback module captures the patient's visual movements during the patient training process and feeds back the visual training results to the processor unit;

[0059] The visual training feedback module collects the visual image sequence of the patient during training through the camera, and uses the image recognition algorithm to locate and identify the key parts of the human body including eyes and hands in the image, and extracts the motion trajectory information of the key parts; the trajectory information is stored in the local database, and different standard action templates are set for different training tasks for comparison and analysis, and the accuracy, speed and amplitude parameters of the action are calculated to form the visual training feedback result data, and transmit it to the processor unit;

[0060] b. The processor unit adjusts the interactive scenario and reallocates the training tasks based on the visual training feedback results sent by the visual training feedback module;

[0061] After receiving the visual training feedback results, the processor unit first evaluates the patient's current training performance according to the preset evaluation rules;

[0062] If the movement accuracy is lower than the set threshold and the speed is lower than the set value, it indicates that the patient has a poor grasp of the current training task; at this time, the processor unit classifies and indexes according to the training difficulty and training goal, searches its internal scenario database for interactive scenarios that are associated with the current training task and are less difficult than the previous one, and reallocates the training task according to the requirements of the new scenario; when reallocating tasks, refer to the patient's previous training information history stored in the local storage module to avoid repeated assignment of task types that have been trained many times and have poor results, and give priority to tasks that have not been trained and have suitable difficulty;

[0063] c. The processor unit sends the adjusted interactive scenario and the reallocated training task to the scenario interactive game module. The user performs corresponding actions according to the new interactive scenario and training task, and repeats steps (1) to (2) until the active training is stopped.

[0064] The present invention has the following beneficial effects and advantages:

[0065] The present invention designs a lower limb intelligent feedback training system with balance training. The system adopts a combination of active and passive training methods. According to the physiological gait curve of the human body, the stepping movement is accurately controlled, so that the patient can gradually "walk" and restore the walking function. At the same time, during the training process, the pressure of the soles of the two feet during the stepping process is detected to analyze the balance of the left and right feet when walking, so as to prevent abnormal gait after the recovery of walking. At the same time, the burden of nursing staff is reduced and the nursing cost is reduced. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 It is a system composition diagram of the present invention;

[0067] Figure 2 It is the interconnection diagram of the actuator of the present invention;

[0068] Figure 3 It is the electronic control system diagram of the present invention;

[0069] Figure 4 It is a diagram of the pressure feedback system of the present invention; DETAILED DESCRIPTION

[0070] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0071] like Figure 1 As shown, it is a system composition diagram of the present invention. The present invention is a lower limb intelligent feedback training system with balance training, including: an electric control system and an actuator connected to the electric control system, a pressure feedback system and a human-computer interaction system;

[0072] The pressure feedback system is used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training, and obtain the pressure value after processing and send it to the electronic control system;

[0073] The actuator is used to control the left and right foot pedals to perform reciprocating motion according to the control instructions of the electronic control system. The electronic control system controls the extension and retraction of the electric push rod to achieve the product's height adjustment, lying and standing, foot extension and retraction, and backrest posture adjustment, so that patients can get in and out of bed conveniently, perform rehabilitation training, and maintain a comfortable training posture.

[0074] The human-computer interaction system is used to receive the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs, and display them in real time; at the same time, it dynamically provides situational interactive voice prompts to enable users to actively train, and uploads the user's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time;

[0075] The electronic control system is used to receive the training control parameters sent by the host computer and control the actuator to perform the corresponding movement; and send the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system to the host computer in real time; at the same time, the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs are displayed in real time on the human-computer interaction system.

[0076] like Figure 2 As shown, it is the interconnection diagram of the actuator of the lower limb intelligent feedback training system of the present invention. The actuator of the product includes two parts: a bed posture adjustment mechanism and a leg training actuator.

[0077] The bed posture adjustment mechanism is used to control the movement of the bed according to the control instructions received from the electronic control system, thereby realizing the change of the bed posture;

[0078] The leg training actuator is arranged at the rear of the bed body, and is used to operate and drive the left and right legs of the disabled patient to perform reciprocating motion according to the control instructions received from the electronic control system.

[0079] (1) The posture adjustment mechanism of the bed body, including: bed body standing push rod, overall lifting push rod, leg adjustment push rod and back adjustment push rod;

[0080] The fixed end of the bed stand-up push rod is installed on the liftable frame of the bed, and the telescopic end is installed on the bed board structure frame, which is used to receive the control command of the electric control system and execute the push rod telescopic action to realize the posture change from lying flat to standing up of the disabled patients on the bed, and then perform leg rehabilitation training after changing to a standing posture;

[0081] The fixed end of the integral lifting push rod is installed on the bottom frame of the bed, and the telescopic end is installed on the liftable frame. It is used to receive the control command of the electronic control system, execute the push rod telescopic action, and realize the overall height adjustment of the bed. It plays a very important role in avoiding the interference and collision between the long telescopic structure of the standing back legs and the ground.

[0082] The fixed end of the leg adjustment push rod is installed on the bed structure frame, and the telescopic end is installed on the telescopic structure of the frame, which is used to receive the control command of the electronic control system, execute the push rod telescopic drive and change the position of the foot pedal, that is, change the distance between the foot pedal and the knee leggings; that is, adjust the distance between the product foot pedal and the knee leggings, and provide the best training accuracy and comfort for patients of different heights and different leg lengths;

[0083] The fixed end of the back adjustment push rod is installed on the bed board structure frame, and the telescopic end is installed on the pitchable structure of this frame. It is used to receive control instructions from the electronic control system, execute the extension and retraction of the push rod, and realize the backward posture adjustment of the back position of the bed board. That is, when the patient stands up on the bed board for training, the back leans backward, thereby obtaining a more comfortable body posture.

[0084] The posture adjustment mechanism of the bed of the present invention can be arranged on any intelligent medical bed, and each push rod is not limited to be installed in the installation position described in the present application;

[0085] (2) The leg training actuator is provided with two drive motors corresponding to the left and right legs of the disabled patient, and connected to the left and right foot pedals respectively;

[0086] The drive motor receives control instructions from the electronic control system, and alternately causes the left and right foot pedals to move up and down, thereby achieving rehabilitation training for the patient's legs to perform stepping and walking.

[0087] like Figure 3 As shown, this is the electrical control system diagram of the lower limb intelligent feedback training system of the present invention. The system core control board serves as the brain of the entire system. It outputs and controls each actuator to perform operations and conduct training, quickly processes and calculates feedback and detection input signals, and conducts real-time data interaction with the host computer.

[0088] The electric control system includes: a core control board and a motor drive board, a push rod drive board, and a signal acquisition interface connected to the core control board;

[0089] The motor drive board is connected to the left and right motors of the leg training actuator to drive the left and right motors to reciprocate, drive the left and right foot pedals to reciprocate up and down, and then realize the rehabilitation training of the patient's legs to step and walk; at the same time, the motor drive board monitors the current of the motor in real time during operation to determine whether the patient has cramps during training. If cramps occur, the training is stopped and the motor is driven to perform slow reverse motion to relieve the cramps;

[0090] The push rod drive board is used to control the extension and contraction of the electric push rod, and monitor the Hall value of the push rod in real time, so as to judge the extension of each push rod, and analyze it into the angle and height of the corresponding bed structure, and display it in real time on the upper computer interface; for each patient, the posture maintained in the training state is recorded according to the usual usage habits, which can be saved as a commonly used posture. When the patient is training, he can execute the usual posture with one button, and then quickly carry out rehabilitation training.

[0091] The signal acquisition interface is mainly used as the data input interface of peripheral sensors. It collects the status information of each module of the product, the position status information of each structure, the plantar training pressure information, safety information, etc. in real time, and transmits it to the system core control board for analysis and processing.

[0092] The host computer communication interface is mainly used for data communication between the core control board and the host computer. The core control board sends information such as the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs to the host computer in real time, and receives the training control parameters sent by the host computer.

[0093] The core control board is used to connect to the host computer through the host computer communication interface, and is used to send the operating status of the training motor, the operating status of each push rod, and the training coordination information of the left and right legs to the host computer, and at the same time receive the training control parameters sent by the host computer to control the actuator through the motor drive board and the push rod drive board.

[0094] like Figure 4 As shown, it is a diagram of the pressure feedback system of the lower limb intelligent feedback training system of the present invention. The pressure feedback system of the present invention comprises: a pressure signal amplifier board, a left leg pressure sensor and a right leg pressure sensor;

[0095] The left leg pressure sensor and the right leg pressure sensor are respectively installed on the pedals of the left and right legs. They are used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training. The pressure signal is then amplified by the pressure signal amplifier board and transmitted to the core control board of the electronic control system for calculation and analysis. By comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are analyzed, and a rehabilitation training plan is specified for the patient. At the same time, the pressure values ​​of the left and right legs are processed by the core control board and sent to the host computer. The pressure values ​​of the two legs will be displayed in real time on the training interface, and the patient's training gait will be displayed through the interface animation, thereby changing the uncoordinated stepping state.

[0096] like Figure 1 As shown in the attached Figure 1 The human-computer interaction system of the present invention comprises: an interactive training module, a processor unit, a display screen, a visual training feedback module, an information storage module and a network transmission module;

[0097] The processor unit is used to receive the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and display them on the display screen; at the same time, adjust the interactive scenario and reallocate the training tasks based on the visual training feedback results sent by the visual training feedback module;

[0098] Interactive training software, installed on the processor unit, including: a situational interactive game module and a visual training feedback module;

[0099] The scenario interactive game module is used to provide scenario interactive voice prompts to enable users to actively train, and at the same time, execute the interactive scenarios adjusted by the processor unit and the reallocated training tasks;

[0100] A visual training feedback module is configured in the interactive training software and is used to capture the patient's visual movements during the patient training process and to feed back the visual training results to the processor unit;

[0101] An information storage module, disposed in the processor unit, for storing the patient's training information, including training status, training progress and rehabilitation status information;

[0102] The network transmission module is integrated in the processor unit and is used to upload the patient's training information to the host computer via Wi-Fi, so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

[0103] like Figure 1 to Figure 4 As shown, the present invention provides a training method for a lower limb intelligent feedback training system with balance training, comprising the following steps:

[0104] 1) The electronic control system receives the training control parameters sent by the host computer, controls the actuators to perform the height adjustment, lying and standing, foot extension and retraction, backrest posture adjustment of the bed, and controls the left and right foot pedals to perform reciprocating motion, so as to realize the user's passive training;

[0105] 2) The electronic control system sends the acquired operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system to the host computer in real time;

[0106] 3) The core control board of the electronic control system sends the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs to the human-computer interaction system; at the same time, the pressure feedback system collects the pressure values ​​of the left and right legs of the left and right foot pedals, and sends them to the host computer and the human-computer interaction system after processing;

[0107] 4) The human-computer interaction system receives the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and displays them on the display screen;

[0108] 5) The human-computer interaction system also provides situational interactive voice prompts to enable users to complete active training, and uploads the patient's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

[0109] In step 2), the pressure feedback system collects the pressure values ​​of the left and right legs of the left and right pedals, and sends them to the host computer and the human-computer interaction system after processing, specifically:

[0110] (1) Pressure data collection and preprocessing:

[0111] The left leg pressure sensor and the right leg pressure sensor monitor the pressure on the pedal in real time at a fixed frequency to obtain raw pressure data; the high-frequency noise components of the raw pressure data are removed by a low-pass filtering algorithm, the pressure curve is smoothed, and the pressure data signal is obtained;

[0112] Normalize the filtered pressure data signal and map the data to a set value range to facilitate subsequent comparison and calculation;

[0113] (2) Pressure signal amplification and transmission:

[0114] The pre-processed pressure data is transmitted to the pressure signal amplifier board, which amplifies the pressure signal according to the preset amplification factor to improve the signal strength and resolution; the amplified pressure signal is transmitted to the core control board of the electronic control system;

[0115] (3) Core control board data reception and analysis:

[0116] After receiving the pressure signal from the amplifier board, the core control board parses the data according to the pre-set communication protocol, restores it to the pressure value information of the left and right legs, and stores it in the buffer for subsequent batch processing.

[0117] (4) Comparative analysis with the preset training model:

[0118] Read the left and right leg pressure data sequence within the set time period from the buffer, and calculate the characteristic parameters of the left and right legs, including the average pressure value, pressure peak value, pressure change rate, and pressure duration parameters;

[0119] Compare and analyze the characteristic parameters of the left and right legs with the standard parameters in the preset training model; the preset training model is established based on the stepping training data of healthy people and patients at different rehabilitation stages, and includes the normal range and change trend of the pressure parameters of the left and right legs at different rehabilitation levels;

[0120] The difference between the left and right leg pressure parameters and the standard parameters is calculated, and the distance between the eigenvectors is calculated using the Euclidean distance formula. The larger the distance, the greater the deviation from the standard state. At the same time, the correlation between the left and right leg pressure parameters is analyzed, and the coordination of the two legs during the stepping process is judged by calculating the covariance. If the covariance is close to 0, it means that the coordination is poor. If the covariance is positive and greater than the threshold, it means that the movements of the two legs are consistent and coordinated.

[0121] (5) Recovery status and coordination assessment:

[0122] According to the difference and correlation results obtained by comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are comprehensively evaluated; if the difference between the pressure parameters of one leg and the standard parameters is greater than the preset value and the other leg is relatively smaller than the preset value, it means that the recovery degree of one leg is relatively backward; if the difference between the pressure parameters of both legs is less than the preset value and the coordination is good, it indicates that the patient's overall recovery state is good; and the evaluation results are graded according to the preset grading standards;

[0123] (6) Development of rehabilitation training plan:

[0124] According to the recovery status and coordination assessment level of the patient's left and right legs, the core control panel selects a training plan from its built-in rehabilitation training plan library; the selected rehabilitation training plan is notified to the patient and the rehabilitation therapist through the display screen or voice prompts, and the patient performs subsequent stepping training according to the plan. During the training process, the system continuously monitors pressure data and adjusts the training plan in real time to adapt to the patient's rehabilitation progress.

[0125] In step 5) of the present invention, the method for implementing active training specifically includes the following steps:

[0126] a. The scenario interactive game module provides users with scenario interactive voice prompts, and users complete active training according to the voice prompts. At the same time, the visual training feedback module captures the patient's visual movements during the patient training process and feeds back the visual training results to the processor unit;

[0127] The visual training feedback module collects the visual image sequence of the patient during training through the camera, and uses the image recognition algorithm to locate and identify the key parts of the human body including eyes and hands in the image, and extracts the motion trajectory information of the key parts; the trajectory information is stored in the local database, and different standard action templates are set for different training tasks for comparison and analysis, and the accuracy, speed and amplitude parameters of the action are calculated to form the visual training feedback result data, and transmit it to the processor unit;

[0128] b. The processor unit adjusts the interactive scenario and reallocates the training tasks based on the visual training feedback results sent by the visual training feedback module;

[0129] After receiving the visual training feedback results, the processor unit first evaluates the patient's current training performance according to the preset evaluation rules;

[0130] If the movement accuracy is lower than the set threshold and the speed is lower than the set value, it indicates that the patient has a poor grasp of the current training task; at this time, the processor unit classifies and indexes according to the training difficulty and training goal, searches its internal scenario database for interactive scenarios that are associated with the current training task and are less difficult than the previous one, and reallocates the training task according to the requirements of the new scenario; when reallocating tasks, refer to the patient's previous training information history stored in the local storage module to avoid repeated assignment of task types that have been trained many times and have poor results, and give priority to tasks that have not been trained and have suitable difficulty;

[0131] c. The processor unit sends the adjusted interactive scenario and the reallocated training task to the scenario interactive game module. The user performs corresponding actions according to the new interactive scenario and training task, and repeats steps (1) to (2) until the active training is stopped.

[0132] In summary, the present invention designs a lower limb intelligent feedback training system with balance training, which has 4 posture adjustment functions, which is convenient for patients to quickly enter the training mode and is convenient for patients of different heights to conduct rehabilitation training. Through active and passive stepping motion training, the physiological gait of the human body during normal walking is simulated, the patient's walking function is restored to the highest degree, and abnormal gait is suppressed. The training process is monitored in real time, and the gait of the lower limbs on both sides can be monitored to assist medical staff in formulating rehabilitation plans more targeted. Through improvement, compensation and substitution, the blood circulation and metabolism of motor tissues (muscles, bones, joints, ligaments, etc.) are improved, neuromuscular function is promoted, muscle strength, endurance, cardiopulmonary function and balance function are improved, etc., to help patients return to their families and return to society.

[0133] The lower limb intelligent feedback training system with balance training of the present invention monitors and collects data on the patient's active and passive training status and the pressure value of the stepping when the legs actively exert force in real time through the force sensor on the sole of the foot during the patient's training process. At the same time, the current of the motor when it is running is monitored in real time through the driver of the reciprocating power source motor. Through the collection and analysis of the above data, the patient's abnormal gait and recovery status are judged, and data-supported disease feedback and rehabilitation evaluation are given. Then, the rehabilitation doctor makes a comprehensive evaluation based on the patient's actual disease state, and then adjusts a more reasonable training plan. At the same time, through the long-term collection of training data of a large number of patients and big data analysis, an evaluation system for rehabilitation training is gradually formed.

[0134] Those skilled in the art will appreciate that the above are only preferred embodiments of the present invention, and the various embodiments of the present disclosure and / or the features described in the claims may be combined or combined in various ways, even if such combinations or combinations are not explicitly described in the present disclosure. It is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art may still modify the technical solutions described in the aforementioned embodiments, or perform equivalent substitutions on some of the technical features therein. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention shall be included in the protection scope of the present invention.

[0135] Although preferred embodiments of the present invention have been described, additional changes and modifications may be made to these embodiments by those skilled in the art once the basic inventive concepts are known. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention. Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A lower limb intelligent feedback training system with balance training, characterized in that: include: Electronic control system and actuators, pressure feedback systems and human-computer interaction systems connected to the electronic control system; The pressure feedback system is used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training, and obtain the pressure value after processing and send it to the electronic control system; The actuator is used to realize the height raising and lowering, lying and standing, footboard extension and retraction, and backrest posture adjustment of the bed according to the control instructions of the electronic control system, and at the same time, control the left and right foot pedals to perform reciprocating motion; The human-computer interaction system is used to receive the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs, and display them in real time; at the same time, it dynamically provides situational interactive voice prompts to enable users to actively train, and uploads the user's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time; The electronic control system is used to receive the training control parameters sent by the host computer and control the actuator to perform the corresponding movement; The operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system are sent to the host computer in real time; at the same time, the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs are displayed in real time on the human-computer interaction system.

2. The lower limb intelligent feedback training system with balance training according to claim 1, characterized in that: The execution mechanism includes: a bed posture adjustment mechanism and a leg training execution mechanism; The bed posture adjustment mechanism is used to control the movement of the bed according to the control instructions received from the electronic control system, thereby realizing the change of the bed posture; The leg training execution mechanism is arranged at the rear of the bed body, and is used to operate and drive the left and right legs of the disabled patient to perform reciprocating motion according to the control instructions received from the electric control system.

3. The lower limb intelligent feedback training system with balance training according to claim 2, characterized in that: The posture adjustment mechanism of the bed body includes: a bed body standing push rod, an overall lifting push rod, a leg adjustment push rod and a back adjustment push rod; The fixed end of the bed stand-up push rod is installed on the liftable frame of the bed, and the telescopic end is installed on the bed board structure frame, which is used to receive the control command of the electric control system, execute the push rod telescopic action, and realize the posture change from lying flat to standing up for the disabled patient on the bed; The fixed end of the integral lifting push rod is installed on the bottom frame of the bed, and the telescopic end is installed on the liftable frame. It is used to receive the control command of the electronic control system, execute the push rod telescopic action, and realize the overall height adjustment of the bed to avoid interference and collision between the leg length telescopic structure and the ground after the bed is standing up; The fixed end of the leg adjustment push rod is installed on the bed structure frame, and the telescopic end is installed on the telescopic structure of the frame, which is used to receive the control command of the electronic control system, execute the telescopic movement of the push rod and change the position of the foot pedal, that is, change the distance between the foot pedal and the knee leggings; The fixed end of the back adjustment push rod is installed on the bed board structure frame, and the telescopic end is installed on the pitchable structure of this frame. It is used to receive control instructions from the electronic control system, execute the extension and retraction of the push rod, and realize the backward posture adjustment of the back position of the bed board. That is, when the patient stands up on the bed board for training, the back leans backward, thereby obtaining a more comfortable body posture.

4. The lower limb intelligent feedback training system with balance training according to claim 2, characterized in that: The leg training execution mechanism is provided with two driving motors corresponding to the left and right legs of the disabled patient, and connected to the left and right foot pedals respectively; The drive motor receives control instructions from the electronic control system, and alternately causes the left and right foot pedals to reciprocate up and down, thereby driving the patient's legs to perform rehabilitation training for stepping and walking.

5. The lower limb intelligent feedback training system with balance training according to claim 1, characterized in that: The electric control system includes: a core control board and a motor drive board, a push rod drive board, and a signal acquisition interface connected to the core control board; The motor drive board is connected to the left and right motors of the leg training actuator to drive the left and right motors to reciprocate, drive the left and right foot pedals to reciprocate up and down, and then realize the rehabilitation training of the patient's legs to step and walk; at the same time, the motor drive board monitors the current of the motor in real time during operation to determine whether the patient has cramps during training. If cramps occur, the training is stopped and the motor is driven to perform slow reverse motion to relieve the cramps; The push rod driving board is used to control the extension and contraction of the electric push rod, and monitor the Hall value of the push rod in real time, so as to judge the extension of each push rod, and analyze it into the angle and height of the corresponding bed structure, and display it in real time on the upper computer interface; Signal acquisition interface, which is used as the data input interface of peripheral sensors, collects the status information of each module, the position status information of each structure, the pressure information of plantar training, and safety information in real time, and transmits it to the system core control board for analysis and processing; The core control board is used to connect to the host computer through the host computer communication interface, and is used to send the operating status of the training motor, the operating status of each push rod, and the training coordination information of the left and right legs to the host computer, and at the same time receive the training control parameters sent by the host computer to control the actuator through the motor drive board and the push rod drive board.

6. The lower limb intelligent feedback training system with balance training according to claim 1, characterized in that: The pressure feedback system comprises: a pressure signal amplifier board, a left leg pressure sensor and a right leg pressure sensor; The left leg pressure sensor and the right leg pressure sensor are respectively installed on the pedals of the left and right legs, and are used to monitor the pressure applied by the left and right feet to the corresponding pedals during the patient's stepping training. The pressure signal is then amplified by the pressure signal amplifier board and transmitted to the core control board of the electronic control system for calculation and analysis. By comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are analyzed, and a rehabilitation training plan is specified for the patient. At the same time, the pressure values ​​of the left and right legs are processed by the core control board and sent to the host computer. The pressure values ​​of the two legs will be displayed in real time on the training interface, and the patient's training gait will be displayed through the interface animation, thereby changing the uncoordinated stepping state.

7. The lower limb intelligent feedback training system with balance training according to claim 1, characterized in that: The human-computer interaction system comprises: an interactive training module, a processor unit, a display screen, a visual training feedback module, an information storage module and a network transmission module; The processor unit is used to receive the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and display them on the display screen; at the same time, adjust the interactive scenario and reallocate the training tasks based on the visual training feedback results sent by the visual training feedback module; Interactive training software, installed on the processor unit, including: a situational interactive game module and a visual training feedback module; The scenario interactive game module is used to provide scenario interactive voice prompts to enable users to actively train, and at the same time, execute the interactive scenarios adjusted by the processor unit and the reallocated training tasks; A visual training feedback module is configured in the interactive training software and is used to capture the patient's visual movements during the patient training process and to feed back the visual training results to the processor unit; An information storage module, disposed in the processor unit, for storing the patient's training information, including training status, training progress and rehabilitation status information; The network transmission module is integrated in the processor unit and is used to upload the patient's training information to the host computer via Wi-Fi, so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

8. The training method of the lower limb intelligent feedback training system with balance training according to claim 1, characterized in that: The following steps are involved: 1) The electronic control system receives the training control parameters sent by the host computer, controls the actuators to perform the height adjustment, lying and standing, foot extension and retraction, backrest posture adjustment of the bed, and controls the left and right foot pedals to perform reciprocating motion, so as to realize the user's passive training; 2) The electronic control system sends the acquired operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system to the host computer in real time; 3) The core control board of the electronic control system sends the running status of the training motor, the running status of each push rod, and the training coordination of the left and right legs to the human-computer interaction system; at the same time, the pressure feedback system collects the pressure values ​​of the left and right legs of the left and right foot pedals, and sends them to the host computer and the human-computer interaction system after processing; 4) The human-computer interaction system receives the operating status of the training motor, the operating status of each push rod, the training coordination of the left and right legs, and the pressure values ​​of the left and right legs fed back by the pressure feedback system sent by the core control board, and displays them on the display screen; 5) The human-computer interaction system also provides situational interactive voice prompts to enable users to complete active training, and uploads the patient's training information to the host computer so that the rehabilitation therapist can monitor the patient's training and rehabilitation status at any time.

9. The training method of the lower limb intelligent feedback training system with balance training according to claim 8, characterized in that: The pressure feedback system collects the pressure values ​​of the left and right legs of the left and right foot pedals, and sends them to the host computer and the human-computer interaction system respectively after processing, specifically: (1) Pressure data collection and preprocessing: The left leg pressure sensor and the right leg pressure sensor monitor the pressure on the pedal in real time at a fixed frequency to obtain raw pressure data; the high-frequency noise components of the raw pressure data are removed by a low-pass filtering algorithm, the pressure curve is smoothed, and the pressure data signal is obtained; Normalize the filtered pressure data signal and map the data to a set value range to facilitate subsequent comparison and calculation; (2) Pressure signal amplification and transmission: The pre-processed pressure data is transmitted to the pressure signal amplifier board, which amplifies the pressure signal according to the preset amplification factor to improve the signal strength and resolution; the amplified pressure signal is transmitted to the core control board of the electronic control system; (3) Core control board data reception and analysis: After receiving the pressure signal from the amplifier board, the core control board parses the data according to the pre-set communication protocol, restores it to the pressure value information of the left and right legs, and stores it in the buffer for subsequent batch processing. (4) Comparative analysis with the preset training model: Read the left and right leg pressure data sequence within the set time period from the buffer, and calculate the characteristic parameters of the left and right legs, including the average pressure value, pressure peak value, pressure change rate, and pressure duration parameters; Compare and analyze the characteristic parameters of the left and right legs with the standard parameters in the preset training model; the preset training model is established based on the stepping training data of healthy people and patients at different rehabilitation stages, and includes the normal range and change trend of the pressure parameters of the left and right legs at different rehabilitation levels; The difference between the left and right leg pressure parameters and the standard parameters is calculated, and the distance between the eigenvectors is calculated using the Euclidean distance formula. The larger the distance, the greater the deviation from the standard state. At the same time, the correlation between the left and right leg pressure parameters is analyzed, and the coordination of the two legs during the stepping process is judged by calculating the covariance. If the covariance is close to 0, it means that the coordination is poor. If the covariance is positive and greater than the threshold, it means that the movements of the two legs are consistent and coordinated. (5) Recovery status and coordination assessment: According to the difference and correlation results obtained by comparing with the preset training model, the recovery status and coordination of the patient's left and right legs are comprehensively evaluated; if the difference between the pressure parameters of one leg and the standard parameters is greater than the preset value and the other leg is relatively smaller than the preset value, it means that the recovery degree of one leg is relatively backward; if the difference between the pressure parameters of both legs is less than the preset value and the coordination is good, it indicates that the patient's overall recovery state is good; and the evaluation results are graded according to the preset grading standards; (6) Development of rehabilitation training plan: According to the recovery status and coordination assessment level of the patient's left and right legs, the core control panel selects a training plan from its built-in rehabilitation training plan library; the selected rehabilitation training plan is notified to the patient and the rehabilitation therapist through the display screen or voice prompts, and the patient performs subsequent stepping training according to the plan. During the training process, the system continuously monitors pressure data and adjusts the training plan in real time to adapt to the patient's rehabilitation progress.

10. The training method of the lower limb intelligent feedback training system with balance training according to claim 8, characterized in that: The step 5) is specifically: a. The scenario interactive game module provides users with scenario interactive voice prompts, and users complete active training according to the voice prompts. At the same time, the visual training feedback module captures the patient's visual movements during the patient training process and feeds back the visual training results to the processor unit; The visual training feedback module collects the visual image sequence of the patient during training through the camera, and uses the image recognition algorithm to locate and identify the key parts of the human body including eyes and hands in the image, and extracts the motion trajectory information of the key parts; the trajectory information is stored in the local database, and different standard action templates are set for different training tasks for comparison and analysis, and the accuracy, speed and amplitude parameters of the action are calculated to form the visual training feedback result data, and transmit it to the processor unit; b. The processor unit adjusts the interactive scenario and reallocates the training tasks based on the visual training feedback results sent by the visual training feedback module; After receiving the visual training feedback results, the processor unit first evaluates the patient's current training performance according to the preset evaluation rules; If the movement accuracy is lower than the set threshold and the speed is lower than the set value, it indicates that the patient has a poor grasp of the current training task. At this time, the processor unit classifies and indexes according to the training difficulty and training goal, searches its internal scenario database for interactive scenarios that are associated with the current training task and are less difficult than the previous one, and reallocates the training task according to the requirements of the new scenario. When reassigning tasks, refer to the patient's previous training information history stored in the local storage module to avoid repeatedly assigning tasks that have been trained many times and have poor results, and give priority to tasks that have not been trained and have appropriate difficulty; c. The processor unit sends the adjusted interactive scenario and the reallocated training task to the scenario interactive game module. The user performs corresponding actions according to the new interactive scenario and training task, and repeats steps (1) to (2) until the active training is stopped.

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